Design Strong App Architecture - 5 Simple Steps To Help You Dominate The Mobile App Market
How can app developers ensure their success in a highly competitive mobile app market? Mobile applications are an integral part of people's lives. From keeping in touch with loved ones to ordering food, mobile apps are used for everything. With the increasing competition in the app market, it’s no longer enough to just have a functional mobile app. So, what does it take to dominate the mobile app market? In this article, we will explain why a strong app architecture is non-negotiable for your app's success and how you can achieve it.
Why is strong app architecture non-negotiable for your app's success?
A strong app architecture is the foundation of a successful mobile app. With a strong app architecture, you can save both time and money in the short and long term. Having a strong Architecture implemented in your app brings many benefits to the project and engineering teams, for example:
- It improves the maintainability, quality, and robustness of the overall app;
- It allows the app to scale. More teams and team members can contribute to the same codebase with minimal code conflicts;
- It's easier to test. A strong architecture encourages simpler types which are generally easier to test;
- Bugs can be investigated methodically with well-defined processes.
How can you achieve a strong app architecture?
Here are some key steps that you should follow:
Step 1: Define your app's requirement
This exploratory phase will help you identify the key features of your app and the data it will handle. At a basic level, it involves having a clear understanding of the project's goals, target users, and commercial objectives. This will help you to map out specific features and functionality. One of the key things to understand is whether the app you are about to build will be an offline-first app or a real-time app as that will have major implications.
Android.com describes an offline-first app as an app that is able to perform some or all of its business logic offline. A great example of an offline-first app is the New York Times app. Users can download the content when they have an internet connection and access it later, even without an internet connection. On the other hand, real-time app architecture refers to designing an app that relies heavily on user behaviour to function.
Let’s dive into the architecture for these two types of app types in a little more detail:
Offline-first app architecture
This approach requires a different app architecture than a traditional online app. Understanding the implications of designing an offline-first app is important to ensure that the app is robust, reliable, and can provide a good user experience even when there is no internet connectivity.
One of the primary implications of offline-first app architecture is that the data layer becomes a crucial component of the app. Since the app will be working with local data most of the time, it’s important to design the data layer to handle reads and writes efficiently. The app should be able to retrieve data for use by other parts of the app, as well as persist user input for later retrieval.
Another implication of offline-first app architecture is the need for efficient data storage and synchronization. Offline-first apps typically rely on caching to help users access data offline. However, the way data is stored, synced, and accessed can vary depending on the server type, architecture, and device. Therefore, it is important to choose an appropriate approach for storing and syncing data to ensure that the app functions smoothly even without an internet connection.
Real-time app architecture
This is an application architecture model where a system responds to a user request in near-real-time. There are several architecture models that can be used for real-time apps, including event-driven architecture (EDA).
The main implication for developers when designing a real-time app architecture is to choose the appropriate technologies and frameworks that can handle high concurrency, low latency, and event-driven processing as the system needs to be able to process and respond to user requests in real time.
Liberty Rider is an example of a real-time app architecture. This app is optimized for motorcyclists and provides a platform where users can plan their routes, navigate, and even export a GPX file for external GPS devices like Tomtom Rider or Garmin Zumo. The app continuously enriches its roadbook platform with contributions from its users. It also features a safety function where the app texts the user's loved ones at the start and end of each motorcycle ride, and they can follow the rider live during their trip.
Step 2: Choose the right app architecture
Once you have defined your app's requirements, you need to choose the right app architecture. There are several app architectures available such as MVP (Model-View-Presenter) and MVVM(Model-View-ViewModel).
MVP and MVVM are both popular architectural patterns. MVP was initially introduced in the 1990s as an evolution of the traditional MVC (Model-View-Controller) pattern, with the main goal of decoupling the view and the model. The presenter acts as an intermediary between the view and the model and is responsible for handling user input, updating the model, and updating the view accordingly.
MVVM, on the other hand, was introduced in the mid-2000s as an evolution of MVP, specifically for WPF (Windows Presentation Foundation) applications. In MVVM, the view and the model are still decoupled, but the presenter is replaced by a view model that provides a layer of abstraction between the view and the model.
The primary benefit of MVVM is that it allows for better separation of concerns, which makes it easier to maintain and test the application. The view model handles the presentation logic, while the view is responsible for rendering the user interface, and the model contains the data and business logic. This separation of concerns makes it easier to modify or replace one part of the application without affecting the other parts. Additionally, the use of data binding in MVVM allows for automatic updates of the UI when the data changes, which can save time and reduce errors.
One potential issue with MVVM is that it can lead to increased complexity, as the view model can become a complex intermediary between the view and the model. Additionally, data binding can sometimes result in performance issues, especially with large data sets.
MVP, on the other hand, is simpler and easier to implement, making it a good choice for smaller projects or teams with less experience. However, it can be more difficult to test and maintain as the project grows. Ultimately, the decision to use MVP or MVVM should be based on the specific needs and requirements of the project, as well as the development team's preferences and experience. Some developers may prefer MVP because it is simpler to implement, while others may prefer MVVM for its greater separation of concerns and testability
Step 3: Design your app's data flow
An app's data flow refers to the movement of data through the different components of your application from the source to display and how that is structured. It includes everything from API response to the data model and finally to the rendering of the data. When a user interacts with an app, data is generated and passed between the different components of the app, such as the UI, the application logic, and the database.
The architecture of an application can directly influence its data flow. In a modular architecture, an app is broken down into smaller modules or components, each of which is responsible for performing a specific function or handling a specific task. These modules communicate with each other through well-defined interfaces and protocols. This modular approach can make the app's data flow in a more streamlined way as it allows the app to process data more quickly and efficiently because the workload is distributed across multiple modules. And since each module is designed to handle a specific function, it’s easier to identify and isolate issues that may arise in the data flow. This means you can troubleshoot and resolve issues quicker, minimizing downtime and improving the overall performance of your app.
On the other hand, in a traditional monolithic architecture, all the data processing tasks are typically handled by a single application. This can lead to a bottleneck in the system as the app tries to process a large volume of data.
To design an app's data flow, developers should first identify the different components of the application that interact with data, such as the UI, the application logic, and the data storage. You should then map out the flow of data between these components, taking into account any transformations or processing that takes place along the way.
For an offline-first app, the data flow design starts with the data layer and revolves around the two main operations - reads and writes. In this approach, data is retrieved from the local storage to be used by other parts of the app. During the initial sync, the app downloads and persists the data in the local storage, which can take a few minutes or longer, depending on the offline profile configured. The offline-first approach heavily relies on the app's data storage, retrieval, and persistence.
On the other hand, in a real-time-first app, the design of the data flow depends on the type of data and how it is accessed. In this approach, data is accessed in real time through an internet connection, and the app is built around the assumption of a stable internet connection. The app's architecture is designed with the primary goal of delivering data in real time with minimal latency. The data flow revolves around real-time events, and the system should be designed to handle data in real-time and display updates in real-time, just like Liberty Rider does.
Step 4: Choose the right technology stack
When assessing the risk of adopting a new technology stack, developers should consider several factors, such as the maturity of the technology, its stability, and the availability of support and resources. When our lightweight and super-fast DI framework, Koin was launched, developers were rightly skeptical. It was new and unfamiliar, and developers were hesitant to adopt it due to any number of risks it posed. It obviously also lacked community support and resources available to help them troubleshoot issues and optimize their use of the framework. And how did they know it wouldn't break their code? Koin was able to demonstrate to developers that the risk was so low, you could even forget you were using it, and it couldn't impact your code.
It was a similar story for Rx Java. If you were around back then(was it 2017 already?), you will remember that initially, when Rx was first introduced, developers were hesitant to adopt it. It’s a powerful tool, but still developers were concerned about the learning curve and the lack of understanding of its potential benefits. It was in the middle of your data exchange and would be difficult to replace if you wanted to, so the stakes were high!
Despite its initial challenges, RxJava has gained a reputation for being a powerful tool for building complex and reactive applications. A lot of developers have come to appreciate its ability to handle complex data flows, manage concurrency, and facilitate the creation of responsive and scalable user interfaces.
Today, it's true that the trend is to replace Rx with Coroutines, as a significant number of teams are still finding Rx too difficult to master and Coroutines perform the same function, but in a more elegant manner.
While Coroutines offer many benefits, there have still been some concerns about adopting them. Here are some common worries:
- Learning curve: Some developers may find it challenging to understand the concept of coroutines and how to use them effectively. It may take some time to learn the new syntax and the different ways to use them.
- Debugging: Debugging coroutines can be more challenging than debugging traditional code, but definitely less so than Rx. Developers may still experience some difficulty tracing the flow of execution and identifying issues.
- Integration with existing codebase: Coroutines may not easily integrate with existing codebases, especially if they rely heavily on callbacks or other asynchronous patterns. Developers may need to refactor their code to use coroutines effectively
Step 5: Understand the Impact of architecture on your app's UI/UX choices
While app architecture does not have a direct impact on UI/UX design, it does indirectly contribute to the quality of the user experience by providing a solid foundation for developers to build upon. By separating the responsibilities of different parts of the app, such as data management, logic, and presentation, developers can focus on the individual components and make design choices that optimize the user experience.
For example, a modularized app architecture can help developers achieve a cleaner separation between the presentation layer and the rest of the app, making it easier to change the UI/UX components without affecting the underlying code. This can lead to a more flexible app that can be adapted to user feedback and evolving business requirements.
On the other hand, a poorly designed app architecture can limit the ability of developers to make changes to the UI/UX without affecting the rest of the app. For instance, tightly coupling the presentation layer with the business logic can make it difficult to change the UI/UX without affecting the underlying code, leading to a less flexible app that is difficult to maintain and scale.
A well-designed app architecture can make all the difference in the success of your app. Strong app architecture is non-negotiable. It ensures that your app is scalable, modular, and easy to maintain. By following the steps mentioned above, you will be way on your way to achieving a strong app architecture and dominating the mobile app market.